Hey HN, Eric Zhang here, formerly YC W11, current CTO @ Scalable Press. I’m posting because we are bootstrapped and profitable, and we’re hiring software engineers. To give you an idea of what you’d do, one engineer on our team wrote an API that helps print over 10,000 shirts a day. Our stack is node, react, angular, and mongo.

We may have already answered your questions about us on http://scalable.press/product-engineer/. It covers hiring process, engineering culture, past projects, and future projects you might work on with us.

Interested? Email me and mention you’re from HN. No need to send a resume—I’d like to hear about what you’ve been working on lately, and feel free to include any relevant project links.

Our goal is to take the risk and complexity out of construction and remodeling by providing homeowners with all the information they need to make great decisions. To get there, we put the product first and are passionate about building something people love and want to use.

Headquartered in a beautiful office in downtown San Francisco, our diverse company includes an economist who lectures at Berkeley, a licensed general contractor, game designer turned marketer and a team of talented engineers.

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Data Engineer #1 - Full Time - competitive salary / generous equity

We're looking for a talented data engineer with experience in large data sets, to take ownership over our system that collects, analyzes & publishes the data.

In this role, you’ll be working throughout the stack to move our consumer marketplace site forward. Responsibilities will range from server configuration to front-end implementation and everything in between.
We're looking for someone that will jump at the opportunity to take ownership of product features that drive traction, which will be used by tens of thousands of users each day.

DotDashPay (https://dotdashpay.com) is a hardware and software platform that makes it easy for machine builders and designers to connect their machines to payments. Our long-term goal is to enable a completely autonomous economy by providing companies with tools that make it simple to build machines that automate the transaction process. We’re a venture backed company with a strong founding team from UC Berkeley (our founders grew out of the CS PhD program).

We’re looking for a full stack developer who wants to develop extremely reliable, clean, well-tested, and downright beautiful systems. We’ve found that a very productive and powerful way to do this is to write code that writes our code for us: autogeneration is the foundation of DotDashPay, and in this paradigm you can become a 100x engineer (building on top of our autogenerators will allow you to ship new features in hours instead of weeks).

On top of our autogeneration framework, we write most of our complex features in a combination of C, C++, and Go (golang). We are currently using Node.js as our web backend language and are migrating our frontend to React. Strong experience in at least a couple of these languages, and the desire to learn the others, is important to us.

Desirable characteristics:

* Polyglot programmer: we have APIs in almost every major language that are autogenerated from our specification. The APIs require small glue code that is written in the target language and needs to conform to the standards / conventions of that language.

* Experience building/managing infrastructure: as a small team, everyone helps build and manage our infrastructure. We use many modern tools and services (Docker, Ansible, AWS) and strive to build things the Right Way™, so we’re always open to trying a new ideas and tools.

* Security experience: our payment systems must support some of the biggest names in retail, and our codebase undergoes rigorous security testing and certifications. A strong understanding of security best practices helps ensure that our products ship faster and our customers can rely on our software.

* Experience / interest in payments: payments is a surprisingly fascinating and complex iceberg. Even if you know very little now, a desire to learn more is important as it pervades most of what we do.

Please email Sean Arietta via sean (at) dotdashpay (dot) com to set up a time for an initial chat.

Why should students have to put up with exorbitant prices for boring test prep classes and books that might not even work? Our mission is simple: create products that give students everywhere access to enjoyable, affordable, and quality test prep. We help millions study at their own pace, on their own time regardless of location, social status, or background.

We’re looking for a Senior Software Engineer to help us improve our products, shape engineering process, and help us grow our small (currently just Zack and I!) but impactful engineering team. So far we use Rails, PhoneGap + Angular, and ReactNative. We’re hosted on AWS.

You have many of the following...

* 3+ years of software engineering experience

* Experience building and releasing web and/or mobile applications

* Experience interviewing software engineering candidates

* A passion for making a difference and leveling the education playing field

The Voleon Group is a technology-driven investment firm employing cutting-edge statistical machine learning techniques. We are looking for an exceptionally capable software engineer. You will architect & implement new production trading systems, machine learning infrastructure, data integration pipelines, and large-scale storage systems.

We seek candidates with a proven track record of writing correct, well-designed software, solving hard problems, and delivering complex projects on time. You should preferably have experience designing and implementing fault-tolerant distributed systems. Experience with building large-scale data infrastructure, stream processing systems, or latency-sensitive programs is a bonus.

Help us build SimCity for real! We help urban planners answer questions like "where should we put housing and jobs for the next 1.5 million people in California?", "what are the carbon impacts of adopting this transit policy?" and "what will the average commute time be in the year 2040?".

To answer these questions faster and in more detail we're hiring software engineers to build the next generation of UrbanFootprint, the world's most sophisticated urban planning and data analysis platform.

Our specific hiring needs at the moment include:

* Senior front end engineer to help direct a greenfield single page app project

* Mid-level to senior back end or full stack engineer to build the backend storage, query, and analysis components of the app

Our stack is rapidly evolving but you'll be sure to run into at least:

* Greenfield projects using ReactJS + MapboxGL

* Python + Postgres/PostGIS

* Large-scale data acquisition, storage, versioning

* Data analysis using tools like Apache Spark

We have real clients, are well funded, offer competitive compensation, a fantastic location in Berkeley, CA, stock options, and a chance to be part of something in its early stages.

The Voleon Group is a technology-driven investment firm employing cutting-edge statistical machine learning techniques. We are looking for an exceptional researcher.

We are a science-driven systematic trading firm, built on the principle that statistical machine learning provides the best solutions to the scientific problems we must solve.

We are looking for a PhD-level scientist to join us in developing predictive models and other components of automated trading systems. You will apply modern statistical machine-learning methods to large, high-dimensional data sets. The work will range from data preparation to model development to production software implementation.

We are successful and growing. Willingness to take initiative, and a gritty determination to productize, are essential.

We hire on the basis of exceptional talent. If you excel in a technical field such as statistics, mathematics, computer science, engineering, or operations research, then we encourage you to contact us.

The following criteria, while not all requirements, illustrate the demands of this role: + Background in modern statistical methods / machine learning